Course: Programming 3 credits: 5

Course code
BFVM23PROGRAM3
Name
Programming 3
Study year
2023-2024
ECTS credits
5
Language
English
Coordinator
F. Feenstra
Modes of delivery
  • Lecture
Assessments
  • Programming 3 - Assignment

Learning outcomes

  1. You demonstrate a high level of competence in applying python and relevant libraries as well as appropriate mathematical, and statistical methods to effectively identify patterns, causal relationships, and actionable insights. 
  2. You develop a maintainable and effective (pre-)processing and evaluation pipeline for time series and or signal data and streaming data. You adhere to the fair principles. Your code is organized, well written, well documented, traceable via version control management systems, and suitably licensed.  
  3. You can integrate diverse knowledge domains, effectively handle complexity, and extract meaningful information from data, even in the presence of incomplete or challenging datasets.  
  4. You adeptly select appropriate data analysis methods, provide sound justifications for your choice, or creatively adapt existing methods to develop solutions for the problems.  

Content

This course teaches practical skills for processing and analyzing time-series, streaming, and signal data using popular data science tools such as Jupyter Notebooks, NumPy, Pandas, and Bokeh. Throughout the course, you will practice programming techniques for loading, cleaning, analyzing, and visualizing streaming data, with an emphasis on creating maintainable solutions. By the end of the course, you will have a solid understanding of the data processing pipeline and be able to handle diverse streaming data, conduct exploratory data analysis, and create effective visualizations. The course is designed to equip you with the skills needed to work with complex data and provide new insights as a foundation for future research and exploration. 

Included in programme(s)

School(s)

  • Institute for Life Science & Technology
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